AI & ML Ops
Put AI to work on your data — without losing control of it.
We take AI from pilot to production on infrastructure you control: secured by your identity, logged end to end, measured for cost, and running on the model you choose.
The problem
AI pilots are easy. Production is where they stall.
The demo works on someone's laptop. Then come the real questions — and without answers, the pilot stays a pilot.
?Where does our data go?
?Who can see the answers?
?What does each answer cost?
?What happens when the model is wrong?
?Is our data already going into personal chatbots?
Shadow AI
Give people an approved route. Close the risky ones.
When nothing better is on offer, staff paste customer data into personal chatbots. Company Windows laptops we manage already block personal browser sync and unapproved extensions. We add an approved assistant behind your own login, so people get the help they want and the data stays inside your controls.
What we build
Five ways to put AI to work.
Predictive analytics & BI
Forecasts and dashboards from your own data, with pipelines that are versioned and repeatable.
Chatbots & NLP
Assistants for customers or teams that read documents, sort requests and hand over to a person when they should.
RAG systems
Answers grounded in your documents, with citations — and each user sees only what they’re already allowed to read.
AI agents
Agents that act in your tools — tickets, reports, workflows — with limits, approvals and every action logged.
ML Ops
Training, deployment, monitoring and retraining as a pipeline, not a person.
Your model, your choice
Self-hosted or cloud. Controlled either way.
Release gates
Nothing goes live until these are true.
Better than today
Beats or matches the current version on an agreed test set, within the cost and speed targets.
Rebuildable
Recreated from the repository: same code, same data version, same results.
Reversible
Rolling back to the previous version is tested and written into the runbook.
Signed off
A named owner on your side approves the release, and the approval is recorded.
Built on the same foundation
AI that inherits everything else we build.
How we start · One use case, in production
Have an AI idea stuck in pilot?
Pick the problem worth solving first. We build it, run it, measure it — then you decide what's next.